Color features play a very important role in the analysis performed by intelligent surveillance systems, such as in forensic searches using various analytics and algorithms. These systems sometimes utilize a large number of cameras. A challenging issue in the analysis performed by these intelligent systems is finding the best matches of objects with similar colors. For example, in order to make sure the objects tracked across cameras are the same objects, color features of the objects are compared. Only objects with similar color features are considered matched objects and are tracked across cameras in the system. In the case of forensic searches where an exemplary object is provided for the search, the system identifies objects with similar color features and provides them as search results.
In these exemplary applications, as well as others, color matching presents a significant challenge. The color temperatures of the cameras in the system may be different due to the color gain adjustment in the white balance processing. In general, proper camera white balancing takes the “color temperature” of a light source into account, which refers to the relative warmth or coolness of white light. Digital cameras can create blue, red, or even green color casts to the image captured by the camera. Since the cameras monitoring even the same field of view may use different white balance parameters and generate images with different color temperature, it is possible that the colors of the same object are dramatically different from camera to camera. Accordingly, there has been a need in the industry for a method and system of providing consistent color of an object across cameras in the system to facilitate analysis of the objects.